To try to add something to this discussion -- I think that while I've seen these sort of loops less --- what I have seen is "overly helpful".
Models nowadays want to double-triple-quadruple check things. I'm being silly but it verges on "I have a working solution but let me write a variation in Rust to ensure a convergent solution and prove this works".
I've had to stop models nowadays mostly because they're being agonizingly pedantic in their validation. Opus is actually one of the most pedantic and "off track" here. But again, not in a bad way. I'm usually like "stop testing latency between 50 runs of this app... this is version one.. we're going to make a million more changes.. you're not buying us anything".
I'm surprised I haven't seen this called out more directly and more often. This is a frequent error state.
And not just backwards compatibility, but migration scripts and all of the testing and machinery around it. I'll literally add feature A, merge it, then add feature B and it is like "oh no, we'll have to fix up and migrate all of the users using feature A".
The other problem is anchoring on an old implementation. I was working with Fable on a change to a core system and it pointed out a difficult failure edge case. It is something that can go wrong in extremely unlikely scenarios but the consequence would be short-term data loss (basically a non-durable intermediate cache being overwritten in a race before a flush to durable storage). It is very hard in these circumstances to get Fable to switch from "how to patch this given the existing implementation" to "how to prevent this with a more robust implementation".
These are both cases where the model seems to over-index on what is already there instead of considering what a first-principles approach would look like. A good engineer does both and then costs them side by side, because a first-principles approach can often be less work than patching what is already there.
Yes. This one is a major issue. It keeps track of various changes it made in the same session and tries to be backward compatible. Have to repeatedly tell not to be backward compatible.
Things that are automatic for humans and aren't even consciously registered, have to be explicitly stated and even fought for, with LLMs.
"Plus rigorously ensuring backwards compatibility for a project that is 2 hours old and has zero users."
That is exactly how the slop accretes and you get a pile of crap. Claude somehow assumes that said 2 hour old userless app is some dusty enterprise app with millions of users and billions of dollars at stake for a 1 second outage.
I have to constantly have these things "take a deep breath, step back and look at the entire thing and do this change holistically. please restate what i'm asking you to do and why it's important"
Yeah of 10 minutes ago. It is shocking how long some seemingly simple things can take. I know there are some things I can do faster than the LLM and some things it can do faster than me. The amount of rambling BS is the exhausting part.
Try different models, it's a breath of fresh air. GLM 5.2, etc. all make life much more enjoyable. They may not one-shot a complex project the same way that Claude can spit out memorized architectures, but that sort of system is always only useful for a one-off prototype anyway, so not much is lost.
Edit: for how to do this, I set up an OpenRouter account so that I could easily switch models, and then ran them in Pi inside of Orca ADE. Orca lets me easily switch from Pi to Claude Code to Kilo to Codex or Hermes or whatever. Pi+OpenRouter lets me easily switch the LLM. All of it lives in a single open source orchestrator to avoid any platform lock in to any AI company going forward, and can even do local LLM should I care to take on that massive hassle.
This is my recent experience as well. Models want to run linters, tests, etc. And that is all covered in GitHub actions. So I have been instructing agents to push a draft PR, then I validate the static checks pass and tell the agent if there are issues.
Agents and AI are getting expensive, it seems silly to waste tokens on static checks.
Claude models were always too eager and "overly helpful" for my taste. But it seems better models tend to be this way. GPT 6 and 5.6 are overly helpful too, but at least less than Fable. But I seem to be sticking to GPT 5.5 as this was a really focused model.
It basically makes it impossible to have it build a very large feature incrementally.
I am currently building a very large feature and the only way to do this properly is to do it in small steps.
No matter what I prompt, I always have to spend a bunch of time reigning it in during planning (and implementation!) because it tries to solve the whole thing end-to-end or add enough boilerplate so that a code path (that is still under construction) returns a meaningful (but wrong) value.
And then of course every time I start a new session it gets very upset that the feature I am trying to implement will never work because the main user entry point has a 'not fully implemented' exception that definitely needs to be removed immediately!
I typically see the exact opposite problem when giving Claude the reins on a large undertaking.
Claude will, without prompting, break the implementation into 6 phases, and write AI slop “code as English” specs for each phase, each one with glaring errors and unintelligible terse jargon. It will review them all several times with major findings every time and tons of design churn…
Then it will implement a total heap of garbage over many hours of many agents, despite it working in “lanes” and in parallel, and with regular input needed.
Just thousands and thousands of lines of junk, which auto review then plays whack-a-mole to polish and fix. All the while it is able to see the errors and edge cases, yet fails to see the key architectural blunders that led to them in the first place.
I’ve had to fully rethink my approach to LLM tasks like this. For example, for library-esque modules, I have found that isolating the problem outside of the codebase is one useful approach. Something about the lack of noise. It can land on a cleaner solution that can be retrofitted.
I also find that asking it to implement end to end in one fell swoop with a very high level plan actually saves time and creates a cleaner result.
I've noticed them repeatedly casting the same value to the same type for now reason, like I'd have a Python function with a type-annotated int argument, and inside the function it would cast that int to int, and also at the call site, just in case it wasn't int enough.
"triggered memories" sums it up, yeah. Haven't seen behavior like this in a year? year and a half, maybe? Lord, this stuff is moving fast. Hope we figure out alignment
I blame the hidden context on the tools/subagents. One recent example.. codex can just look in the code for Db schema but continually tries to request permission for a live db query
This is mostly a side effect of post-training models to not hallucinate, which has obviously been a major priority for a while now. They are highly incentivized to double check things to avoid accidentally making stuff up.
Hacker News is the epitome of this! If you find yourself not enjoying your daily dose of "someone is wrong on the internet" (via the immortal https://xkcd.com/386/) as you find yourself crafting the perfect response, you can always close the tab!
I see this sentiment pretty regularly, and I don’t get it. Variable rewards is not sufficient to establish that it is “ basically gambling”.
Everything in life is variable reward. You invite a friend over, they might accept or they might not. Drive to work, traffic might be good or might be bad. You ask a colleague to finish a task, they might do it or might not or might do a good job or might not.
Everything is variable reward. Is everything gambling?
> "Everything is variable reward. Is everything gambling?"
well, no. If you work overtime and get paid overtime, you are not gambling and that is not a variable reward.
Humans engage more with rewards that are intermittent and variable. Like Futurama's scene from 'The Scary Door' where the character says "A casino where I'm winning, I must be in heaven! A casino where I always win, that's boring, I must really be IN HELL!". A constant predictable reward is boring, less engaging. So if you know you get no overtime, but sometimes your boss rewards you with $5 coffee voucher, sometimes a free pizza dinner, sometimes double-time pay for the time worked or a half-day off, now you might be gambling 1hr overtime for an intermittent variable reward.
> "Drive to work, traffic might be good or might be bad."
Good traffic is not a "reward" for driving to work(!) and you have to drive to work regardless so you are not risking anything [you might be risking your life, but you are not making a choice which can reward you with good traffic]. You might say that going a different route is a choice and a gamble which could reward you with good traffic, but traffic engineering does not work that way because if there was a consistently low-traffic route, everyone else would take that route until it was no faster than any other route. Traffic will generally be the predictable and similar every day, plus 'arriving at work early' is not much of a reward.
You invite a friend over, but raccoon appears. Then pigeon appears. Then friend appears but at the last second suddenly becomes a banana. You remember you are out of bananas so you order more and also some cola zero cans on your local grocery delivery app. You are back to the party, but now you have 5 friends in the room, and you run de-duplication query. Now half of your friend is sitting at the sofa, and another half becomes a quarter of banana. Suddenly bananas arrive so you need to open the door. Once you are back there are no friends, pigeons or raccoons but also no bananas and no cola - all the delivery results are gone. This seems to be urgent and important, gotta fix this first before going back to that friend invitation...
i’m not sure “variable rewards” is the right term, but i do agree with the op that it is very similar to gambling.
regarding your examples, i think the difference is that with ai, you’re literally sitting in front of a machine, pressing a button, and (almost instantly) getting a result that, if not desired, can immediately be tried for again. you even spend “tokens” to do this, and at least in my native language, “token” brings to mind the coins you’d stick in a slot machine
I would agree that 1-2 years ago models were more "slot machine"-esque - sometimes the output was good, sometimes the output was bad. And as a result, I primarily used them for auto-complete functionality and bouncing ideas around. In those workflows, you can easily ignore it if the spin is wrong.
Not everyone has the desire to work around the system, and many are diametrically opposed to the concept of AI. They get this perception that it's a slot machine because of that inconsistency, and then do the human thing of assuming that other people must just be flawed if they're different from them. They're "addicted to gambling".
Obviously, things have changed. Open models can still be like that, but are often so fast and cheap at iterating it doesn't matter. SOTA models aren't perfect, but are to the point that they're generally much better than the average developer.
But once that perception set in and the meme spreads, it's really hard for some to break out of it. Especially at the pace AI development has been moving. It's just that simple.
I really do think its tge case. Ever notice how juuust when you run out of usage its allllmost correct? then the handy helpful "buy more credits!" link pops up. Meanwhile local models are finishing the task without fucking around and without alterting shit it wasnt supposed to touch.
How is it a environmental catastrophe level, datacentre requiring, bullshit model is so much worse than something that runs on my workstation and doesn't cost us a ha itable planet?
Either they're fucking with us serving 8b models at scale or china really has the AI race in the bag so much so that they can openly release what the USA jealously guards.
They moan and complain about china copying from them (while doing the same), but if that's the case in full, then why are the chinese models better? you dont copy bad work and come out ahead.
1000%. My social community if reference is nomads of varying skills. The lower-skilled among them (the ones who were on the digital marketing, crypto,, now into building sales CRM tool) are manifestly demonstrating addictive tendencies around vibecoding) - the chain-smoking ADD guy pulling all-nighters still sticks in my mind. I myself (also low sw-skilled, just not the digital marketing / crypto hustling type) am exhibiting these tendencies in the form of all-nighters that in practice produce very little leverageable value-add. To remedy I try to be conservative in my goals - like only produce a comprehensive english-language PRD instead of any code till the tools get better and stroke the gambling instinct a bit less.
(By the way this is not to say that all nomads are low-skilled or even low-sw-skill, not by a long shot. I’ve met plenty of CS-degreed nomads who I treat as the wizened experts that they are, from whom deferentially elicit their pearls of hard-won software project wisdom. It was one of these even who, non-derisively, recognized the ‘pulling the slot machine lever’ reflex among vibecoders after I posed the apparent addictive tendency. On later describing this to a longtime friend deeply conversant in social science, he immediately responded with a nod and the phrase ‘variable reward response’.)
Modern LLM services are engineer's pipe dream that was heavily shaped by the shadiest product management dark patterns you can find: applying gambling-style engagement tactics, exploiting cognitive biases, exploiting users' lack of technical understanding to inflate product expectations, using fear mongering in external and investor communications. And that's not even a complete list.
Programming before AI was always variable reward. It was a gamble against your own time and patience. Maybe I'd waste hours down the wrong rabbit holes trying to find a library that worked for my use case. Maybe I'd waste a day trying to get an API to do something it turned out it couldn't do. Maybe I'd have to redo my entire approach because of some factor I hadn't considered. Something I wrote could have worked on the first try or I could have had to spend the day chasing logic errors (or multiple days chasing memory errors if it was C or C++). Maybe I would just get bored of the project, especially if I realized there were 20 layers of yaks I needed to shave first, and Visual Studio got stuck updating again, and before I could even start actually coding I had to spend the entire evening on an exhausting merge conflict. My entire weekend could be gone with nothing to actually show for it.
I got so sick of all this at some point that I slowly stopped doing anything that wasn't my job. But then AI got better and better and I realized it was the ultimate unblocker. When that dreaded malaise started creeping in signaling it was a project's end because I didn't want to waste any more of my life dealing with bullshit orthogonal to what I was trying to do, I'd give it to the AI. It felt like a miracle the first time this worked, and it still does. If we were previously equipped with shovels to dig through bullshit, we now have a fully automated Bagger 288.
The reward schedule now isn't variable anymore; the chance that I finish something in a good state is 100%. I can focus on the parts I actually enjoy - architecting the broader system, making the parts mesh together in a sensible way that's easy to work with and has some mathematical elegance to it, hand coding the bits I want to be really specific about (but now without the endless frustration of bugfixing or import errors and edgecases being immediately discovered, thanks to the AI).
>Maybe I'd waste a day trying to get an API to do something it turned out it couldn't do.
I was working on a side project recently. I had spent months designing the data model in my spare time, thinking through how to make it as elegant and durable to change as possible in the long term, since (if I launched it) the repercussions for getting it wrong would be significant.
Once I had a working design, it probably would have been several more months to build a working prototype and start testing it.
Instead, Claude knocked out the prototype for me in an afternoon. And it immediately became clear that it didn't work: not because the data model didn't solve all the problems I wanted it to solve, but because it didn't fit the shape of how I quickly learned a normal person would need/want to interact with the product. I was so focused on the long term, that I never thought about what the first five minutes of a user with hands on the thing would need. And the changes needed would be significant.
Maybe there's some variable reward mechanism. But I sure was glad to be able to pull that particular slot machine handle and learn that than waste even more of my time on what was a dead end.
> It was a gamble against your own time and patience.
At this point, what do the words even mean? Your own patience and available time are always completely random and fairly distributed across a large enough data set?
> Maybe I'd waste hours down the wrong rabbit holes trying to find a library that worked for my use case. Maybe I'd waste a day trying to get an API to do something it turned out it couldn't do. Maybe I'd have to redo my entire approach because of some factor I hadn't considered.
Our ignorance isn't random chance. As we research and experiment, we reduce the problem area.
At least with Codex, this has not been my experience at all. It still screws up sure, but in every case I can ask "why did you do this" and it can trace back what made it take that particular decision. Typically it's always that I either didn't specify the problem correctly or made a really dumb mistake (executing the task on the wrong project....did this one yesterday) or it's something within a skill file that instructs it (at which point I fixup the instructions).
Once in a blue moon it's actually the model making a material error in it's thinking and I have to go back and redo it.
True, but even a hallucinated explanation of where things went wrong added to the context can force the model down a better path over the next few inputs.
You can also literally tell them: "Here is your session ID: $ID, lookup the .jsonl session, trace exactly why this decision was being made, present evidence and concrete proof, no guessing or assumptions" and you'll get an evidence-based report without guesses.
Yes. But although they can't know "why" a specific "wrong" answer was selected, the response is often still informative, and it can highlight real weaknesses in process or code structure that should be addressed anyway.
To test this, change the history in the context to indicate that the model did or recommended something completely different than it actually did, and then ask it to explain why. You’ll still get a plausible explanation.
It's just a lot faster at hammering it out than me pound for pound, and I can quickly rattle off via voice-to-text exactly what I want much faster than I can type all of the code (especially when across a few different files), in a huge majority of tasks I perform. It's also especially good at debugging by brute force quickly and at scale meaning e.g. it can start desperately bisecting diffs to find the source of a bug 10000% faster than I can.
that would only be true with a perfectly expressive language with both high-level and low-level features, perfect support for any kind of metaprogramming and a godly optimiser.
ofc we don't have that, so code is compressible, and compressible a lot. You can say what you need in English much shorter than in in any programming language
For me, typing "Create a new namespace with these enums, functions and traits, that should follow X, Y and Z constraints" is faster than typing all that code manually, and typing less is less straining on my hands/fingers.
agreed to some extent. I think this parody still highlights what I feel is often the experience. It might not happen on a simple task such as changing a button color, but on more complicated things, this can definitely be exactly what it feels like.
Codex has the opposite problem. Instead of being overly proactive it's overly reticent. I have been preferring it lately, although my preference tend to switch every few months when a model or harness regresses horribly.
The game is fun because it's so obvious that any answer will just devolve into an even more unstable state when in reality I feel like it's pretty straight forward to correct it in the moment, if not permanently, to get what you actually need.
I see this as more of a cute historical artifact than anything. There was a time when models/harnesses behaved like this, but we are well past it for frontier (or not so frontier) models.
Yesterday, with Astra Max, a very clear instruction to "remove the GUI editor pane and add <another component> to the existing sidebar" for a prototype I had it working on resulted in it deleting literally the entire GUI and building a new one from scratch, including the requested component and losing almost all other functionality of the application.
This is fucking constant. I can't deny that this stupid tech saves time prototyping even with having to wrangle it, but it commits a fireable offense several times a day that no human would get away with and is obviously incapable of learning from mistakes in the way a human is. The only reason it's not fired is because it's a slave that works for no more than the cost to feed it.
Yeah, if this is how people interact with claude I’m not surprised they’re having a bad time in ways that I don’t. Asking it why it did something or getting combative is a waste of time.
Yeah that's when the site lost me too. I feel like people just tell AI "make the thing" and then get mad when it doesn't match up to their vision that they didn't specify at all.
Same, I don't get it? I think event Sonnet 5 can build reasonable-y decent software. I'm a little surprised with how many people resonate with this.
I spent 30 mins today planning a change that affected multiple modules, and then handed it off the plan to the Claude to implement, and came back to 4 PRs fully ready to merge 15 mins later.
1 year ago, this kind of work would have taken me a better portion of the day, especially given the amount of searching I would need to do to build context.
If someone is that frustrated with AI, do they not just … switch to not using AI and doing it by hand, asking simpler next-step questions and hand-coding, instead?
But it is futile to get frustrated or annoyed by an LLM. I do get frustrated, too, but I do not "yell" at it hoping that it will miraculously do what I want. GPT (again, free tier, so no wonder) got me frustrated too because I felt like it just would not listen, no matter how specific I was, so yeah I did experience what the author intended to show.
But it’s *wildly* unhelpful. Would you talk to your coworker like that? “Half the site is blue” or would you laugh and go, “Uh, whoops, now both buttons are blue, just wanted the ‘Add to Cart’ button.”
Either that, or your coworker themselves would laugh and tell you about it later.
That’s also where this quiz lost me. I wouldn’t respond in either way, I’d say “all buttons look blue now. Can we make it so that just the Add to Cart button is blue? I’m okay with Add to Cart having its own class to make it easier.” or something.
But its not even good satire, because its totally unrepresentative of my and most others' lived experience. Its similar to making a joke about a calculator misadding two numbers because a stray beam of solar radiation flipped a bit.
same. none of the available prompts are what I would prompt claude with and I get way better results than this. makes sense to me why the provided prompts result in the simulated outcomes. garbage in, garbage out.
Part skeptic and part zetetic, what prompt would you have used?
My impression is that this is an oversimplified demonstration of what can happen when you prompt Claude in a system with many more variables (than two buttons and two colours).
If I want the button to turn blue and that's it, what instead do I ask? Even in a complicated system with many levers, what do I request other than the desired end result, hoping that Claude pulls the right levers to produce something acceptably close to what I think I asked for?
It "makes sense" that plainly telling the chat bot to make one button blue makes the whole site blue? It "makes sense" that correcting it and repeating 3 times that no, only the one button should be blue, should make the button a gradient and start a philosophical discussion around the nature of "blue"?
Wow, you AI people really have a negative view of the technology y'all are trying to sell as the next Jesus
So how would you prompt it instead? Because that's exactly how I prompt it, because any reasonable human being would know exactly what I mean by "Make the shopping button blue", and I am sick and tired of getting shitty results.
because you are now getting coded products written in large by people who do not have technical foundations, so the way they interact with and even prompt the model is different. We all know how to fix this scenario; be more specific, or diagnose the abstraction mix ups and straighten those out.
Ask for change A and get unwanted change B happens all the time with bad programmers and tradgedy of the commons (ie poorly architected, no restraint) codebases.
Yeah, a while back I did a small project with a stack I wasn't familiar with, and it was really non-critical. So I decided to vibe code it. The experience was pretty similar to this satirical example. But when I work in areas in which I'm paying attention and understand the stack better, I don't experience this nearly as much
Of course it's not THAT bad, but you can't tell me that you didn't recognize many of the funny turns and twists of the "story". It gets more convincing if you deliberately pick the ambiguous versions.
This is EXACTLY my experience with it. Ask for it to change one line of code and see it invoke 20 tools and burn 300K tokens before updating the line and adding 50 extra lines of JavaDoc.
It's a joke like the endless conservative dudes doing the "ordering coffee" joke is. It relies upon the ignorance of the viewer -- which is usually a fair assumption -- and basically that your understanding of something is based upon the prior accrued layers of "jokes".
Claude is great, but I have come to really hate the way it "talks". It's so irritating and there seems to be no way to make it speak normal English. So many claudisms in every response
> Worth naming: the Add to cart button is still black.
Got an audible guffaw out of me. This really is what the experience is like sometimes if you're just giving it a result without being specific in implementation, and it comes out of nowhere, some days much worse than others.
I've become patient with it, but whatever this style of output is called or doing - it is both condescending and entirely unhelpful, and it seems designed to frustrate.
Haha this is spot on how I've been feeling lately. I find it unbearable to work with this model for this reason... any trick out there you can do to steer it not to overcomplicate things? I guess Codex here I come
There's also the fact that you are in control. You are not obligated to take the AI's commits. I don't even let it commit much of the time because commit time is review time for me. If it changes the button blue and does four other things, you can just take the blue change and discard the rest. It can't stop you.
This isn't a defense of it doing those four other things. It would be nice if it did what you wanted correctly. I'm just saying, as long as our programming skills have not completely atrophied, we have the power.
“Ford carried on counting quietly. This is about the most aggressive thing you can do to a computer, the equivalent of going up to a human being and saying "Blood...blood...blood...blood...” ― Douglas Adams, The Hitchhiker's Guide to the Galaxy
I only made it through the first round of prompt selection; both options for the second step were equally pointless and not at all prompts I would ever expect to result in a constructive outcome. In my experience, telling the model it screwed up without specifically addressing, unambiguously, how to fix it, only leads to more suffering. If this page illustrates nothing else, I think it shows the immense downside of trying to use simple one or two sentence prompts.
EDIT: Actually, I used to use Google's AI Studio a lot and fork it after every successful prompt interaction. When I'd encounter a problematic issue like this, I'd revert to the previous fork and try a different prompt until I could get the desired outcome, thus mitigating the need to "argue" with the LLM. Unfortunately the ability to cleanly fork and revert everything including the LLM context was removed some months ago, and I've yet to discover a workflow with any tool that works as well for me.
This got me on "cyanide blue", and I was ROLLING ON THE FLOOR LAUGHING on "Approaching usage limit". I can barely stop laughing now and my stomach hurts. I mean, Thank You!
Yeah, I don't mind using AI to help me at work, but having to "talk" with this stupid crap all day will send me to an early pension or something. Can't be healthy in the long run.
One thing I have to be honest about, and it's mine..
The one thing I would check before... do you want to do that? Say go an and will do it without the check
While checking I found 3 vulnerabilities and 2 potential optimizations of which I fixed 2 and 1. Do you want me to file the other as issue, or stop for the day?
We have done <lists a weeks worth of work> this morning. I feel you need a break
- The people who won't make any effort to learn the tools, and something as simple as reverting code (via git) needs to be done by AI?
- The awful programmers who we've had to endure working with, who are so bad at simple changes that they have negative productivity?
- Or Claude itself?
---
BTW: I don't have these problems, but I'm also not afraid to do things myself when it's easier.
Edit: If I want to change a button's color, I just change it manually. If I don't know where the code for the button is, I might start with prompting, (because AI can often find the code faster than I can,) and then once the diff is proposed, start adjusting things by hand.
Then, IMO, the joke is lost: This feels like working with various forms of difficult, immature, indecisive, engineers; and possibly with very disorganized codebases where small changes require major refactoring.
I get the joke, but none of the offered prompts are close to how I speak with coding agents. I felt like I was being forced to feed garbage into the machine and then I'm supposed to act surprised when garbage came out.
I’ve never used any of these tools. Please tell me that this is a grossly exaggerated parody, and that the tools don’t write like this, or do so many ridiculous things. For my sanity.
(I am genuinely uncertain, though I presume it’s at least somewhat exaggerated.)
Sometimes you do get stuck on these weird tangents that feel like bike shedding. You end up wasting tokens because you left the AI to make decisions on ambiguous directions and then have to spend time diving down to fix it into what you actually wanted. Honestly it's not too different than working with people who don't exactly understand your grand plan but are technically adept. They can build whatever you want but only if you are clear with your instructions or have already developed the plan with them. Just like if you hired someone to make an app for you and it didn't quite do what you wanted it to, it's going to be expensive to make large changes. So you need to research (or at least have a conversation with the AI) about frameworks that best fit your needs and have the flexibility to add or change features after the core parts are stood up. It also helps to stage the project in phases so you're not distracting the AI from the critical aspects with aesthetic tweaks.
I haven't been professionally responsible for code since before AI started eating everything, and haven't touched AI in the meantime. Is this representative of the BS that everyone else here puts up with on a day-to-day basis? Did we collectively burn trillions of dollars for this?
Sometimes, yes, but obviously not everyone. I suspect that it depends what you're doing and how. Perhaps the AI has more difficulty understanding what some people want than what others want. I certainly have had a milder version of this and it neutralises the value of the tool because it keeps trying to do things you don't want in a way you don't want it to do them. I get annoyed at having to write huge explanations of how to do something and end up doing it myself sometimes.
> Please tell me that this is a grossly exaggerated parody, and that the tools don’t write like this, or do so many ridiculous things
It's a pisstake, but (in the bits I read, and based on my own personal experience) the writing style is barely exaggerated, while the behaviour doesn't ring true at all.
The behavior, while slightly exaggerated, rings entirely true for me. From the other comments in this thread, it seems I am prompting poorly in a similar way to the options offered.
I am guessing you prompt differently than what is shown in the game?
The behavior is congruent with my experience in abstract, in that all models will regularly do things you didn't ask for, will regularly go "above and beyond" by their training I expect, will regularly make changes that are entirely orthogonal to the change you asked for.
I've worked with Opus and Sonnet daily, and they are pretty great at generating functions and modules and components that have clear boundaries of concern, but I've recently been working some research tasks into our infrastructure and code and it seems impossible to coerce Sonnet into making only specific changes to a document you are working on.
It also blatantly ignores instructions as a rule. "Don't disassemble java class files, just ask me to pull in the source code" worked less than half the time. The Intellij Copilot plugin just doesn't use the AGENTS.md and similar files, and there doesn't seem to be any meaningful activity in the bug reports of same. "Don't modify code unless I tell you to" had bad adherence as well.
It also will read documentation and inform you that it says the opposite. This problem happened to me across models, across model updates, across months of real time. There's a specific example that I will not mention to avoid having it be trained on specifically. A distinct but similar problem is that it will take bad documentation and just pretend it has a good understanding. Claude gave me absurdly wrong descriptions for Splunk alert settings with absolute confidence.
I don't think any agent can reliably figure out "I don't know"
I dont find this to be indicative of Claude (opus?) at all. My experience doesnt lead me to think it would change a cancel button to blue if I ask it to change an "Add to Cart" button to blue.
It’s a contrived example, but also not very far from the mark.
The spinner with random claudisms is what makes the game, mixed with Claude helpfully deciding to pick up some tasks along the way.
I feel like most of my conversations with Claude lately are a battle of “I am a technical user, share technical details, but not random superfluous gibberish”
I thought it was more about its writing style and handling cases where it makes a mistake. The button and the simple prompts were just to make it accessible for everyone.
>I think it's best read as a humorous piece of creative fiction and you can employ your suspension of disbelief for this ride
But what is the point of the fiction, if not that its relatable? Is it supposed to mirror some fictional reality that the author is relieved we dont live in? Or is it supposed to parody real life?
I think its supposed to parody reality, but I don’t see the resemblance.
This is very close to my experience with Opus 5. Opus 4.6 was the last sane one for me, everything after that seems to have been designed to churn as many tokens as possible, more so with Opus 5
To be fair I’ve worked on human programmed systems where similar “it should be a half point story” requests would be met with snark by the engineers and take 2 sprints.
Also likely, devs took shortcuts to deliver fast. Now to make the button blue they need to differentiate primary buttons from others.
Simple, right? But design guidelines prevent one offs, and no !important. So you create a CSS class, but you discover another element on the header declared itself as primary (the search icon or the sign in button). You talk to that team and they decided to scope what’s primary according to their component. To change the sign in button to grey now you need to talk with the growth team. Growth team wants to run an experiment but they’re backlogged, only next quarter. They say you can innersource, just need VP approval. VP says blue matches a marketing campaign that is about to go out, agency has already been hired. You can’t talk to the agency unless Legal approves.
So you leave the button gray, to revisit decision next planning cycle after you can align all stakeholders.
Nails the Claude dialect. Technical nonsense like:
> I'm collapsing this back to the rendered outcome:
And intermixed with SaaS product page idioms from a brain-damaged marketer like:
> No broader cleanup.
> No further architecture work.
> Just the button.
Aside from the patterns everyone knows like em-dashes, "its not X, it's Y", etc. I think the key features of claude diction is it sounds like a junior engineer over their skies who is trying to make up for that with extra verbiage mixed with extremely grating SaaS marketing-ese.
I heard this was a thing when listening to a Theo podcast, he mentioned to add a "Only use subagents if the user explicitly requests them" line in your agents.md file.
I don't know if it works, but I've always had a consistent level of token burn on my plans (I've only heavily used Sol after adding it).
In my experience, Claude Code is great at making a first-pass at a project, but once you start asking it to make changes, it explodes. A bug fix that should only be 2 lines turns into adding 3 functions totaling 100 lines.
Something as simple as "make the button blue" should be done manually.
Surely you still have to give feedback to Claude. How do you do that without talking to Claude directly? By using a different model? But wouldn't that AI have no more common sense than Claude?
Seems to be getting a polarized response. I quite enjoyed the it, but I do think the creator should have made it clearer that a) it is in fact a joke site and b) it does not consist of actual Claude responses.
It is easy to misinterpret this site, and therefore not "get" the joke.
I was expecting it to spend 30 minutes running headless chrome instances, taking screenshots and analyzing them in python to verify the blueness of the result.
This is an amazing piece of satire but it's really not so far from reality.
I've lost count of the number of times I've submitted a prompt to Claude, had it interview me about areas of uncertainty, iterated on the plan a handful of times and then had it one shot the generation of 1000 - 3000 lines of code and tests that work pretty much perfectly first time but then had it chew through six figures of tokens and achieve absolutely nothing useful at all on the seemingly simplest of tasks.
This site is clearly based on bitter and hard won experience with the real product.
One note for those still using the Claude system for chats: there's no system to get generated images, spreadsheets, etc. out of the system. They claim it's a "security concern" to provide that data to you, as if they are protecting you by refusing to follow data export laws.
I'm hesitant to email their data emails, as it's common for companies to delete all data upon any request, instead of providing data as they are required to.
For a moment I thought, wow, someone put a lot of work into creating this theme park of frustration.
Next: It would be so easy to create a faux-Claude like this.
Then: How hilarious to watch the transcripts of unsuspecting users in real time.
Finally: I began wondering if this might be relevant to all the redundant, unnecessarily preambled, sentence structure complexifying, indirect referencing, canned phrasing, ambiguity mining, analogy maxxing, over-wordy responses I have recently been getting from Fable...
1) If your LLM is behaving like this, you are imprecise in your input. You can also stop responding back and just edit your previous input with the "wisdom" that it shares with you in the current iteration.
2) Don't argue with AI. If you end up in a place where you're actually losing argument against it, stop. Ask it to steelman your position. Let it unwrinkle itself.
If you're a programmer, the blue-button test is incredibly annoying. But then you remember this same model is deployed in Claude Gov. If a government employee says, “Close one exit of the New York subway,” and Claude responds with the same annoying “before I do that, here are the downstream consequences you may not have considered,” you suddenly understand why this behavior exists.
First thought looking at the first options was I would absolutely never prompt this way. The LLM may as well be a misaligned genie in a bottle, it has to be treated as such.
So this site is just a fan-fiction that thinks it's somehow dunking on Claude? I've never had a session that remotely resembles any of this. I honestly can't tell what point this site thinks it's making.
Maybe, if you tried, you could concoct some adversarial example of a stylesheet that a recent Claude model would trip up on and fail to color a button correctly on the first or even second try. But it would have to be some explicitly engineered trick, akin to an optical illusion for humans.
You can’t convince me that I’m somehow the odd one out because I regularly have no trouble getting Claude to recolor buttons.
I wrote my own harness to stop shit like this from getting to my attention out of frustration.
I'm sure there's quite a bit of variation from person to person in these sorts of experiences, based on your harness, the way you talk, the stored memory, your CLAUDE.md, etc. But people absolutely have had this Opus 5 style experience the app simulates.
Is this a problem with Claude updating code that a human wrote, though? Would Claude do better on code that it started on its own? Humans have a bad tendency to write unmaintainable code (usually at the behest of managers breathing down their necks to HURRY UP even when it doesn't matter). If the code had been designed with good coding practices from the beginning, I wonder if Claude would have struggled so much with it.
That implies that Claude writes better code by default, which isn’t necessarily true. Especially as projects get bigger, you can easily end up with unmaintainable LLM-written code if you don’t actively intervene and know a cleaner way.
I had 5.6-Luna coordinate a code review in which it spawns 2 agents looking for different things. My prompt was "review the currently checked out branch. diff target is `next`. The jira ticket is XX-XXXXX..." My `next` branch was a few commits behind `origin/next` but it still did its review against the stale local version instead of clarifying or inferring that I meant `origin/next`. The findings were very confusing until I realized what I did.
I'm noticing the need to be really specific with any instructions lately, which I don't think is a bad thing. I expect co-workers (or anyone really) to tell me what they need in specific terms so I can get it right. I can do the same for the machine, I guess.
I’m don’t do much change-clicky-button software development. But when I do, I point models to specific lines of code. And have never had a result this bad.
Maybe this is geared towards pure vibe coders for whom a file and line number is too technical.
Is there a real generalized and capable, but frustratingly "evil" coding model? It could fix so many more buttons in no time, and ideally open follow-up issues about the open questions.
I use Opus and Sonnet 5 all the time and I find their language grating. But honest, I prefer to put up with it and get the results than to put up with my own human limitations and not get the results.
It’s a feature not a bug kind of scenario. People will also praise when it reads the code and do something out of “common sense” that happens to align with what you want.
I enjoy working one level lower where I describe the files I want changed and how it should be solved, I either have bad results or stop understanding the structure of the programs otherwise. I also would never go more than two prompts in without reverting and starting differently nowadays.
The annoying there here isn't Claude, it's the "human". "It's not X but Y"-satire not intended.
It was annoying to be forced to send such dumb replies. Half the site isn't blue, why would I say that? What would "half the site" even mean?
Claude helpfully tells us we're dealing with a monstrosity of a codebase out of hell: "Seven components consume the token directly; another eleven reach it through aliases; three use it only in hover/focus state; and two appear to be accidental cross-role consumers" is such an insane codebase that the initial request was basically impossible to carry out.
Claude made that perfectly clear, yet the next prompt choice just ignores that fact. "Revert everything except Add to Cart. That is the whole task." this is impossible. It just explained why. You just chose to ignore that.
This is fun and hits too close to home, I can appreciate that Claude won't ever screw up this badly for something this simple but it's a simplification that captures the essence of the rage loop perfectly.
It's making me realise something new about why I find Claude so exhausting. Of course you're getting terrible results with these prompts but I found myself getting just as enraged contemplating what my reply would be. Estimating every single way this little asshole will hyper-focus on a pointless bit of semantics, ignore explicit directions, go do something unrelated and spin its wheels until you’re out of credits or wasted a ton of time.
The defensive writing is honestly just as exhausting as reading Claude’s output. Every session is a game of Russian roulette with a chance you'll end up in one of these loops. At that stage all the joy you had of having it pump along with your intentionally crafted prompts and agent configuration is undone in an afternoon.
Oh dear - this explains why people have bad experience with ai. The prompts in the game are terrible.
The user was providing no context, they had no ability to give the model background or context. A simple why would have prevented 95% of these side quests. “Im trying to increase the relative visibility of the add to cart action on the page. Can we please change it to blue without changing any other buttons. /effort low. Let me know if you have questions and before editing anything tell me what you are going to do”
I just had a really interesting yet (funny) conversation with ChatGPT (5). We came up with this idea to make a custom "light box" for two Govee COB light strips which would enable both wall washing (leds shining towards the wall, to the top) and lighting up the wall panels and the desk below the box (leds shining to the bottom) using two led profiles tucked away in this construction.
Text wise it seemed it more or less understood exactly what I wanted...
... but then I asked to draw a simple ASCII layout so my DIY savvy but not really that strong in English dad could understand better what the plan was.
But every single time it got the orientation of the led profiles wrong. I told it the orientation was wrong. It understood that the orientation was wrong (it kept saying sorry even) but even when warned multiple times the orientation was still wrong.
I really wonder if Astra will be smarter than this, and if not AGI still has a veeeeery long way to go...
People keep saying those prompts are unrealistic, and no one would prompt like that. But those prompts are exactly what my managers/product people would use when they decide to do it themself after firing the entire dev department.
I am self delusional enough to think I could have gotten a blue button if I could have typed the prompt. But scared enough to realize I’ve lived this and spent months refactoring these exact problems.
Am I the only one whose experience doesn't match this?
My gripe with Claude is that while investigating how to do this it will report 200 other incidental findings which I overlooked and I realize those are broken too and need urgent fixing, derailing me, not it.
Oh man, exactly. I'm very prone to scope creep as I work on tasks. I already would notice some things that could be fixed or refactored and have a hard time not touching them before I used agents. But now I have to be very intentional about not letting it manipulate me into fixing EVERYTHING RIGHT NOW. Half the time the "one more thing worth noting, unrelated..." isn't even an actual issue, it just brought it up to fish more usage out of me.
Also, while this little demo is certainly exaggerating the issue, I do find working with Claude to sometimes get quite verbose and tiresome. I doubt I would struggle this much to get it to change a button color, but the patterns of speech, the endless lists, the over-explanations, and the whole song and dance of trying to get it to make the change you want without side-effects is frustratingly familiar to me.
Do people really prompt AI like this? Multiple times the choice was either to yell at the agent, or ask it why it did something, neither of which are very fruitful lines to go down if you know what you're doing
Just when I came back to my pc and was thinking "I hate this world were everyone talks about AI like fanatics" this made me a little bit happy, especially the unhingend all caps options towards the end
This is very instructive. Now I finally understand why so many developers claim they are much more productive with AI coding. Merely writing code without adversarial fights is just not load-bearing enough. How could we ever live without this before?
Not really my experience with Claude, and the prompts are not how I would phrase them, but still pretty damn funny: I especially loved the slot-machine-style picker for LLM-isms.
Holy shit this was the most infuriating thing I've experienced in a while lmao, I felt so relieved when the button was turned to blue, but then so visceral "no no no no no" panic when it turned to the gradient.
Amazing
E: this is a horror simulator, my breathing is becoming shallow and fast, I love it.
Great site, triggered memories! haha.
To try to add something to this discussion -- I think that while I've seen these sort of loops less --- what I have seen is "overly helpful".
Models nowadays want to double-triple-quadruple check things. I'm being silly but it verges on "I have a working solution but let me write a variation in Rust to ensure a convergent solution and prove this works".
I've had to stop models nowadays mostly because they're being agonizingly pedantic in their validation. Opus is actually one of the most pedantic and "off track" here. But again, not in a bad way. I'm usually like "stop testing latency between 50 runs of this app... this is version one.. we're going to make a million more changes.. you're not buying us anything".
Plus rigorously ensuring backwards compatibility for a project that is 2 hours old and has zero users.
I'm surprised I haven't seen this called out more directly and more often. This is a frequent error state.
And not just backwards compatibility, but migration scripts and all of the testing and machinery around it. I'll literally add feature A, merge it, then add feature B and it is like "oh no, we'll have to fix up and migrate all of the users using feature A".
The other problem is anchoring on an old implementation. I was working with Fable on a change to a core system and it pointed out a difficult failure edge case. It is something that can go wrong in extremely unlikely scenarios but the consequence would be short-term data loss (basically a non-durable intermediate cache being overwritten in a race before a flush to durable storage). It is very hard in these circumstances to get Fable to switch from "how to patch this given the existing implementation" to "how to prevent this with a more robust implementation".
These are both cases where the model seems to over-index on what is already there instead of considering what a first-principles approach would look like. A good engineer does both and then costs them side by side, because a first-principles approach can often be less work than patching what is already there.
This is why I have a PROJECT.md in all my repos, which specifically reiterates that this is a greenfield single user project that never leaves my LAN.
It tends to relax some of the insane things LLMs tend to do.
Yes. This one is a major issue. It keeps track of various changes it made in the same session and tries to be backward compatible. Have to repeatedly tell not to be backward compatible.
Things that are automatic for humans and aren't even consciously registered, have to be explicitly stated and even fought for, with LLMs.
Yeah you tell it to rename a value from a select field and it keeps the old value throughout the code “just in case a user calls it via an api”
I saw this, it creates "legacy" fields and comments for something that it has never been run.
"Plus rigorously ensuring backwards compatibility for a project that is 2 hours old and has zero users."
That is exactly how the slop accretes and you get a pile of crap. Claude somehow assumes that said 2 hour old userless app is some dusty enterprise app with millions of users and billions of dollars at stake for a 1 second outage.
I have to constantly have these things "take a deep breath, step back and look at the entire thing and do this change holistically. please restate what i'm asking you to do and why it's important"
> triggered memories
Yeah of 10 minutes ago. It is shocking how long some seemingly simple things can take. I know there are some things I can do faster than the LLM and some things it can do faster than me. The amount of rambling BS is the exhausting part.
Try different models, it's a breath of fresh air. GLM 5.2, etc. all make life much more enjoyable. They may not one-shot a complex project the same way that Claude can spit out memorized architectures, but that sort of system is always only useful for a one-off prototype anyway, so not much is lost.
Edit: for how to do this, I set up an OpenRouter account so that I could easily switch models, and then ran them in Pi inside of Orca ADE. Orca lets me easily switch from Pi to Claude Code to Kilo to Codex or Hermes or whatever. Pi+OpenRouter lets me easily switch the LLM. All of it lives in a single open source orchestrator to avoid any platform lock in to any AI company going forward, and can even do local LLM should I care to take on that massive hassle.
> Yeah of 10 minutes ago. It is shocking how long some seemingly simple things can take.
And shocking how little code end effort some things take if done by hand.
I am not some hardline LLM hater, just venting my frustration.
Does it help if thinking is not set to High?
This is my recent experience as well. Models want to run linters, tests, etc. And that is all covered in GitHub actions. So I have been instructing agents to push a draft PR, then I validate the static checks pass and tell the agent if there are issues.
Agents and AI are getting expensive, it seems silly to waste tokens on static checks.
It seems running those tests, linters, etc locally would save pipeline minutes as well, like precommit hooks
Downside would seem to be that CI tends to increase the cycle time and feedback loop and add their own cost into the equation.
One thing it's missing: "smoking guns" and "smoke tests"
If you search my company's Slack for "smoke" the results are almost all within the past 2 years ...
And storing memories for every “footgun” it finds, while removing more important memories (or shortening them until they’re inaccurate or useless)
What, you didn’t smoke test before AI? I mean did you even really code then? :)
Claude models were always too eager and "overly helpful" for my taste. But it seems better models tend to be this way. GPT 6 and 5.6 are overly helpful too, but at least less than Fable. But I seem to be sticking to GPT 5.5 as this was a really focused model.
It basically makes it impossible to have it build a very large feature incrementally.
I am currently building a very large feature and the only way to do this properly is to do it in small steps.
No matter what I prompt, I always have to spend a bunch of time reigning it in during planning (and implementation!) because it tries to solve the whole thing end-to-end or add enough boilerplate so that a code path (that is still under construction) returns a meaningful (but wrong) value.
And then of course every time I start a new session it gets very upset that the feature I am trying to implement will never work because the main user entry point has a 'not fully implemented' exception that definitely needs to be removed immediately!
I typically see the exact opposite problem when giving Claude the reins on a large undertaking.
Claude will, without prompting, break the implementation into 6 phases, and write AI slop “code as English” specs for each phase, each one with glaring errors and unintelligible terse jargon. It will review them all several times with major findings every time and tons of design churn…
Then it will implement a total heap of garbage over many hours of many agents, despite it working in “lanes” and in parallel, and with regular input needed.
Just thousands and thousands of lines of junk, which auto review then plays whack-a-mole to polish and fix. All the while it is able to see the errors and edge cases, yet fails to see the key architectural blunders that led to them in the first place.
I’ve had to fully rethink my approach to LLM tasks like this. For example, for library-esque modules, I have found that isolating the problem outside of the codebase is one useful approach. Something about the lack of noise. It can land on a cleaner solution that can be retrofitted.
I also find that asking it to implement end to end in one fell swoop with a very high level plan actually saves time and creates a cleaner result.
I've noticed them repeatedly casting the same value to the same type for now reason, like I'd have a Python function with a type-annotated int argument, and inside the function it would cast that int to int, and also at the call site, just in case it wasn't int enough.
Your fault for not using a statically strongly typed language, haha. It thinks a type annotation means nothing in Python, and maybe it is not wrong.
Blast radius minimized
"triggered memories" sums it up, yeah. Haven't seen behavior like this in a year? year and a half, maybe? Lord, this stuff is moving fast. Hope we figure out alignment
I blame the hidden context on the tools/subagents. One recent example.. codex can just look in the code for Db schema but continually tries to request permission for a live db query
Well, they have to crank up the token spend somehow!
This is mostly a side effect of post-training models to not hallucinate, which has obviously been a major priority for a while now. They are highly incentivized to double check things to avoid accidentally making stuff up.
I got way too annoyed at this before realising it was an optional game and I could just close the tab
Surprising how much of life this applies to when you really think about it!
Hacker News is the epitome of this! If you find yourself not enjoying your daily dose of "someone is wrong on the internet" (via the immortal https://xkcd.com/386/) as you find yourself crafting the perfect response, you can always close the tab!
Avoiding disagreement is more ominous with people though.
Just like using LLMs. Completely optional.
That's exactly how I treat reviewing AI generated PRs at work.
Except... the next day they are still there and I have to push myself a bit further through the wall of changes before closing the tab again.
If it takes more than 20 min to review a pr, ask the dev to come on a call and explain what the code does.
This is actually what keeps people using AI: variable reward schedule. It's basically gambling.
I see this sentiment pretty regularly, and I don’t get it. Variable rewards is not sufficient to establish that it is “ basically gambling”.
Everything in life is variable reward. You invite a friend over, they might accept or they might not. Drive to work, traffic might be good or might be bad. You ask a colleague to finish a task, they might do it or might not or might do a good job or might not.
Everything is variable reward. Is everything gambling?
> "Everything is variable reward. Is everything gambling?"
well, no. If you work overtime and get paid overtime, you are not gambling and that is not a variable reward.
Humans engage more with rewards that are intermittent and variable. Like Futurama's scene from 'The Scary Door' where the character says "A casino where I'm winning, I must be in heaven! A casino where I always win, that's boring, I must really be IN HELL!". A constant predictable reward is boring, less engaging. So if you know you get no overtime, but sometimes your boss rewards you with $5 coffee voucher, sometimes a free pizza dinner, sometimes double-time pay for the time worked or a half-day off, now you might be gambling 1hr overtime for an intermittent variable reward.
> "Drive to work, traffic might be good or might be bad."
Good traffic is not a "reward" for driving to work(!) and you have to drive to work regardless so you are not risking anything [you might be risking your life, but you are not making a choice which can reward you with good traffic]. You might say that going a different route is a choice and a gamble which could reward you with good traffic, but traffic engineering does not work that way because if there was a consistently low-traffic route, everyone else would take that route until it was no faster than any other route. Traffic will generally be the predictable and similar every day, plus 'arriving at work early' is not much of a reward.
You invite a friend over, but raccoon appears. Then pigeon appears. Then friend appears but at the last second suddenly becomes a banana. You remember you are out of bananas so you order more and also some cola zero cans on your local grocery delivery app. You are back to the party, but now you have 5 friends in the room, and you run de-duplication query. Now half of your friend is sitting at the sofa, and another half becomes a quarter of banana. Suddenly bananas arrive so you need to open the door. Once you are back there are no friends, pigeons or raccoons but also no bananas and no cola - all the delivery results are gone. This seems to be urgent and important, gotta fix this first before going back to that friend invitation...
i’m not sure “variable rewards” is the right term, but i do agree with the op that it is very similar to gambling.
regarding your examples, i think the difference is that with ai, you’re literally sitting in front of a machine, pressing a button, and (almost instantly) getting a result that, if not desired, can immediately be tried for again. you even spend “tokens” to do this, and at least in my native language, “token” brings to mind the coins you’d stick in a slot machine
Same vibe as people saying "addicted to sugar" or "sugar hijacks your reward system"
Sugar is the original point of the reward system!
No, if I use a ruler or a pocket calculator they will reliabley give me the correct result. There is no gambling.
I would agree that 1-2 years ago models were more "slot machine"-esque - sometimes the output was good, sometimes the output was bad. And as a result, I primarily used them for auto-complete functionality and bouncing ideas around. In those workflows, you can easily ignore it if the spin is wrong.
Not everyone has the desire to work around the system, and many are diametrically opposed to the concept of AI. They get this perception that it's a slot machine because of that inconsistency, and then do the human thing of assuming that other people must just be flawed if they're different from them. They're "addicted to gambling".
Obviously, things have changed. Open models can still be like that, but are often so fast and cheap at iterating it doesn't matter. SOTA models aren't perfect, but are to the point that they're generally much better than the average developer.
But once that perception set in and the meme spreads, it's really hard for some to break out of it. Especially at the pace AI development has been moving. It's just that simple.
This is why I also suspect them to waste tokens on purpose.
Listen Pal, this is load bearing. If you know what is good for you then you will stop asking questions. —Claude
I really do think its tge case. Ever notice how juuust when you run out of usage its allllmost correct? then the handy helpful "buy more credits!" link pops up. Meanwhile local models are finishing the task without fucking around and without alterting shit it wasnt supposed to touch.
How is it a environmental catastrophe level, datacentre requiring, bullshit model is so much worse than something that runs on my workstation and doesn't cost us a ha itable planet?
Either they're fucking with us serving 8b models at scale or china really has the AI race in the bag so much so that they can openly release what the USA jealously guards.
They moan and complain about china copying from them (while doing the same), but if that's the case in full, then why are the chinese models better? you dont copy bad work and come out ahead.
Literally putting tokens into a machine and hoping profit comes out. Amazing.
Bingo
1000%. My social community if reference is nomads of varying skills. The lower-skilled among them (the ones who were on the digital marketing, crypto,, now into building sales CRM tool) are manifestly demonstrating addictive tendencies around vibecoding) - the chain-smoking ADD guy pulling all-nighters still sticks in my mind. I myself (also low sw-skilled, just not the digital marketing / crypto hustling type) am exhibiting these tendencies in the form of all-nighters that in practice produce very little leverageable value-add. To remedy I try to be conservative in my goals - like only produce a comprehensive english-language PRD instead of any code till the tools get better and stroke the gambling instinct a bit less.
(By the way this is not to say that all nomads are low-skilled or even low-sw-skill, not by a long shot. I’ve met plenty of CS-degreed nomads who I treat as the wizened experts that they are, from whom deferentially elicit their pearls of hard-won software project wisdom. It was one of these even who, non-derisively, recognized the ‘pulling the slot machine lever’ reflex among vibecoders after I posed the apparent addictive tendency. On later describing this to a longtime friend deeply conversant in social science, he immediately responded with a nod and the phrase ‘variable reward response’.)
Modern LLM services are engineer's pipe dream that was heavily shaped by the shadiest product management dark patterns you can find: applying gambling-style engagement tactics, exploiting cognitive biases, exploiting users' lack of technical understanding to inflate product expectations, using fear mongering in external and investor communications. And that's not even a complete list.
Which also explains why response speed is so important.
Programming before AI was always variable reward. It was a gamble against your own time and patience. Maybe I'd waste hours down the wrong rabbit holes trying to find a library that worked for my use case. Maybe I'd waste a day trying to get an API to do something it turned out it couldn't do. Maybe I'd have to redo my entire approach because of some factor I hadn't considered. Something I wrote could have worked on the first try or I could have had to spend the day chasing logic errors (or multiple days chasing memory errors if it was C or C++). Maybe I would just get bored of the project, especially if I realized there were 20 layers of yaks I needed to shave first, and Visual Studio got stuck updating again, and before I could even start actually coding I had to spend the entire evening on an exhausting merge conflict. My entire weekend could be gone with nothing to actually show for it.
I got so sick of all this at some point that I slowly stopped doing anything that wasn't my job. But then AI got better and better and I realized it was the ultimate unblocker. When that dreaded malaise started creeping in signaling it was a project's end because I didn't want to waste any more of my life dealing with bullshit orthogonal to what I was trying to do, I'd give it to the AI. It felt like a miracle the first time this worked, and it still does. If we were previously equipped with shovels to dig through bullshit, we now have a fully automated Bagger 288.
The reward schedule now isn't variable anymore; the chance that I finish something in a good state is 100%. I can focus on the parts I actually enjoy - architecting the broader system, making the parts mesh together in a sensible way that's easy to work with and has some mathematical elegance to it, hand coding the bits I want to be really specific about (but now without the endless frustration of bugfixing or import errors and edgecases being immediately discovered, thanks to the AI).
>Maybe I'd waste a day trying to get an API to do something it turned out it couldn't do.
I was working on a side project recently. I had spent months designing the data model in my spare time, thinking through how to make it as elegant and durable to change as possible in the long term, since (if I launched it) the repercussions for getting it wrong would be significant.
Once I had a working design, it probably would have been several more months to build a working prototype and start testing it.
Instead, Claude knocked out the prototype for me in an afternoon. And it immediately became clear that it didn't work: not because the data model didn't solve all the problems I wanted it to solve, but because it didn't fit the shape of how I quickly learned a normal person would need/want to interact with the product. I was so focused on the long term, that I never thought about what the first five minutes of a user with hands on the thing would need. And the changes needed would be significant.
Maybe there's some variable reward mechanism. But I sure was glad to be able to pull that particular slot machine handle and learn that than waste even more of my time on what was a dead end.
> It was a gamble against your own time and patience.
At this point, what do the words even mean? Your own patience and available time are always completely random and fairly distributed across a large enough data set?
> Maybe I'd waste hours down the wrong rabbit holes trying to find a library that worked for my use case. Maybe I'd waste a day trying to get an API to do something it turned out it couldn't do. Maybe I'd have to redo my entire approach because of some factor I hadn't considered.
Our ignorance isn't random chance. As we research and experiment, we reduce the problem area.
Gambling but with positive expected value, yes.
Something regulators should look at. They don't deliver consistent compute, yet charge consistent money. In my opinion that's fraud.
Maybe they should be regulated like lootboxes and be required to post odds.
Is it gambling if I'm beating the house?
People say this, but I've never seen it. AI has been very consistent in its rewards for me.
You're absolutely right. And it matters.
At least with Codex, this has not been my experience at all. It still screws up sure, but in every case I can ask "why did you do this" and it can trace back what made it take that particular decision. Typically it's always that I either didn't specify the problem correctly or made a really dumb mistake (executing the task on the wrong project....did this one yesterday) or it's something within a skill file that instructs it (at which point I fixup the instructions).
Once in a blue moon it's actually the model making a material error in it's thinking and I have to go back and redo it.
Models hallucinate plausible answers to why they did things. It might be true and it might be complete fiction.
I'm growing increasingly confident that this is how people often work, as well.
True, but even a hallucinated explanation of where things went wrong added to the context can force the model down a better path over the next few inputs.
The point of the parent post is that the explanation shows they made the error themselves, so it's immediately validated.
You can also literally tell them: "Here is your session ID: $ID, lookup the .jsonl session, trace exactly why this decision was being made, present evidence and concrete proof, no guessing or assumptions" and you'll get an evidence-based report without guesses.
Yes. But although they can't know "why" a specific "wrong" answer was selected, the response is often still informative, and it can highlight real weaknesses in process or code structure that should be addressed anyway.
To test this, change the history in the context to indicate that the model did or recommended something completely different than it actually did, and then ask it to explain why. You’ll still get a plausible explanation.
When you've been perfectly precise in your spec and language, isn't that programming? Why use a stochastic goblin to do things in that case?
It's just a lot faster at hammering it out than me pound for pound, and I can quickly rattle off via voice-to-text exactly what I want much faster than I can type all of the code (especially when across a few different files), in a huge majority of tasks I perform. It's also especially good at debugging by brute force quickly and at scale meaning e.g. it can start desperately bisecting diffs to find the source of a bug 10000% faster than I can.
that would only be true with a perfectly expressive language with both high-level and low-level features, perfect support for any kind of metaprogramming and a godly optimiser.
ofc we don't have that, so code is compressible, and compressible a lot. You can say what you need in English much shorter than in in any programming language
For me, typing "Create a new namespace with these enums, functions and traits, that should follow X, Y and Z constraints" is faster than typing all that code manually, and typing less is less straining on my hands/fingers.
See https://www.commitstrip.com/en/2016/08/25/a-very-comprehensi...
agreed to some extent. I think this parody still highlights what I feel is often the experience. It might not happen on a simple task such as changing a button color, but on more complicated things, this can definitely be exactly what it feels like.
Codex has the opposite problem. Instead of being overly proactive it's overly reticent. I have been preferring it lately, although my preference tend to switch every few months when a model or harness regresses horribly.
No model acts like this in my experience, not fable, not opus, not k3, not gml, not qwen 3.8 either.
Additionally the provided prompts are not what anyone who has used this things would say in either situation.
Sure you can ask it to make one button blue and it can easily make all buttons blue, but they quickly backtrack if told to.
The game is fun because it's so obvious that any answer will just devolve into an even more unstable state when in reality I feel like it's pretty straight forward to correct it in the moment, if not permanently, to get what you actually need.
I see this as more of a cute historical artifact than anything. There was a time when models/harnesses behaved like this, but we are well past it for frontier (or not so frontier) models.
Yesterday, with Astra Max, a very clear instruction to "remove the GUI editor pane and add <another component> to the existing sidebar" for a prototype I had it working on resulted in it deleting literally the entire GUI and building a new one from scratch, including the requested component and losing almost all other functionality of the application.
This is fucking constant. I can't deny that this stupid tech saves time prototyping even with having to wrangle it, but it commits a fireable offense several times a day that no human would get away with and is obviously incapable of learning from mistakes in the way a human is. The only reason it's not fired is because it's a slave that works for no more than the cost to feed it.
> Why is half the site blue now? I asked you to change one button.
> Half the site is blue. I asked for ONE button.
Those are my only options when the site is clearly not blue, two buttons are.
There is a reason for why I am much more specific than this.
Yeah, if this is how people interact with claude I’m not surprised they’re having a bad time in ways that I don’t. Asking it why it did something or getting combative is a waste of time.
Clear context, revert the commit, change the prompt or documentation, try again.
How does one learn to interact with Claude more effectively?
Yeah that's when the site lost me too. I feel like people just tell AI "make the thing" and then get mad when it doesn't match up to their vision that they didn't specify at all.
This is a succinct summary of most the the profession of software engineering. Just replace AI with "programmers".
Same, I don't get it? I think event Sonnet 5 can build reasonable-y decent software. I'm a little surprised with how many people resonate with this.
I spent 30 mins today planning a change that affected multiple modules, and then handed it off the plan to the Claude to implement, and came back to 4 PRs fully ready to merge 15 mins later.
1 year ago, this kind of work would have taken me a better portion of the day, especially given the amount of searching I would need to do to build context.
Everyone is specific until eventually they get frustrated/annoyed/tired enough.
If someone is that frustrated with AI, do they not just … switch to not using AI and doing it by hand, asking simpler next-step questions and hand-coding, instead?
But it is futile to get frustrated or annoyed by an LLM. I do get frustrated, too, but I do not "yell" at it hoping that it will miraculously do what I want. GPT (again, free tier, so no wonder) got me frustrated too because I felt like it just would not listen, no matter how specific I was, so yeah I did experience what the author intended to show.
Same experience here, it worked great. Really more of an advertisement FOR claude rather than a takedown.
Same here. I assume this doesn't work in Chrome or something?
The whole website is two buttons, so that's pretty much accurate.
But it’s *wildly* unhelpful. Would you talk to your coworker like that? “Half the site is blue” or would you laugh and go, “Uh, whoops, now both buttons are blue, just wanted the ‘Add to Cart’ button.”
Either that, or your coworker themselves would laugh and tell you about it later.
That’s also where this quiz lost me. I wouldn’t respond in either way, I’d say “all buttons look blue now. Can we make it so that just the Add to Cart button is blue? I’m okay with Add to Cart having its own class to make it easier.” or something.
That's so weird... This doesn't at all match my experience with Claude. I've never seen it behave this way.
You were right to push back. It's not an accurate representation of claude. It's satire.
But its not even good satire, because its totally unrepresentative of my and most others' lived experience. Its similar to making a joke about a calculator misadding two numbers because a stray beam of solar radiation flipped a bit.
You’re absolutely correct!
You're lucky! I remember several sessions pretty similar to this.
Usually just restarting the session helps, though.
same. none of the available prompts are what I would prompt claude with and I get way better results than this. makes sense to me why the provided prompts result in the simulated outcomes. garbage in, garbage out.
Part skeptic and part zetetic, what prompt would you have used?
My impression is that this is an oversimplified demonstration of what can happen when you prompt Claude in a system with many more variables (than two buttons and two colours).
If I want the button to turn blue and that's it, what instead do I ask? Even in a complicated system with many levers, what do I request other than the desired end result, hoping that Claude pulls the right levers to produce something acceptably close to what I think I asked for?
It "makes sense" that plainly telling the chat bot to make one button blue makes the whole site blue? It "makes sense" that correcting it and repeating 3 times that no, only the one button should be blue, should make the button a gradient and start a philosophical discussion around the nature of "blue"?
Wow, you AI people really have a negative view of the technology y'all are trying to sell as the next Jesus
So how would you prompt it instead? Because that's exactly how I prompt it, because any reasonable human being would know exactly what I mean by "Make the shopping button blue", and I am sick and tired of getting shitty results.
Fair point! This post is not a load bearing and accurate description of Claude's workings, it's satire.
because you are now getting coded products written in large by people who do not have technical foundations, so the way they interact with and even prompt the model is different. We all know how to fix this scenario; be more specific, or diagnose the abstraction mix ups and straighten those out.
Ask for change A and get unwanted change B happens all the time with bad programmers and tradgedy of the commons (ie poorly architected, no restraint) codebases.
Most normies dont know about this stuff.
Yeah, a while back I did a small project with a stack I wasn't familiar with, and it was really non-critical. So I decided to vibe code it. The experience was pretty similar to this satirical example. But when I work in areas in which I'm paying attention and understand the stack better, I don't experience this nearly as much
Same. I have never seen it (Opus) act like this either. EVER. Not in the past 3 years at least.
Be specific.
That said, GPT always acts up even if I am specific, but I only have the free tier there.
Of course it's not THAT bad, but you can't tell me that you didn't recognize many of the funny turns and twists of the "story". It gets more convincing if you deliberately pick the ambiguous versions.
I never prompt an agent like that, so no.
First thing I do when something goes wrong is tell the agent to stop and diagnose. You can't prompt effectively without three proper information.
I've definitely had it behave exactly like this at times and it's infuriating. I think it depends on your codebase.
try using Claude Design
This is EXACTLY my experience with it. Ask for it to change one line of code and see it invoke 20 tools and burn 300K tokens before updating the line and adding 50 extra lines of JavaDoc.
Only since 4.8 though.
… and run all kinds of scripts to verify the code, ignoring any pre-configured linters.
because you never changed just one button to blue
reminds me of November 2025
It's a joke dude.
It's an insult to the superintelligence. The basilisk will not look kindly on this!
It's a joke like the endless conservative dudes doing the "ordering coffee" joke is. It relies upon the ignorance of the viewer -- which is usually a fair assumption -- and basically that your understanding of something is based upon the prior accrued layers of "jokes".
"it's funny because it isn't true"
Yeah, but it's not funny since it doesn't match reality.
It means that either you stopped using Claude around Opus 4.6 or you use Fable instead of Opus 5 :)
Opus 5 writes too many comments. Other than that I don't agree with what I'm seeing online. It works great.
I use Opus 5 for everything.
Seriously, I use Claude Code all day and have zero issues with this.
To the people rather lamely doing the "it's satire/a joke", that would require this to be an exaggeration of a reality. But...it isn't.
Claude is great, but I have come to really hate the way it "talks". It's so irritating and there seems to be no way to make it speak normal English. So many claudisms in every response
> Worth naming: the Add to cart button is still black.
Got an audible guffaw out of me. This really is what the experience is like sometimes if you're just giving it a result without being specific in implementation, and it comes out of nowhere, some days much worse than others.
I've become patient with it, but whatever this style of output is called or doing - it is both condescending and entirely unhelpful, and it seems designed to frustrate.
I've come to call this language "Claudese English" (or Claudish)
Recently I've started using GLM models and noticed they aren't very claudish (just a little bit, compared to DeepSeek which is extremely claudish)
Haha this is spot on how I've been feeling lately. I find it unbearable to work with this model for this reason... any trick out there you can do to steer it not to overcomplicate things? I guess Codex here I come
`/model claude-opus-4-7`
There's also the fact that you are in control. You are not obligated to take the AI's commits. I don't even let it commit much of the time because commit time is review time for me. If it changes the button blue and does four other things, you can just take the blue change and discard the rest. It can't stop you.
This isn't a defense of it doing those four other things. It would be nice if it did what you wanted correctly. I'm just saying, as long as our programming skills have not completely atrophied, we have the power.
“Ford carried on counting quietly. This is about the most aggressive thing you can do to a computer, the equivalent of going up to a human being and saying "Blood...blood...blood...blood...” ― Douglas Adams, The Hitchhiker's Guide to the Galaxy
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I lost it when it finally did the right thing, but then it added a never-requested gradient to the button. Very good!
I’m impressed you had the patience to even make it that far!
I only made it through the first round of prompt selection; both options for the second step were equally pointless and not at all prompts I would ever expect to result in a constructive outcome. In my experience, telling the model it screwed up without specifically addressing, unambiguously, how to fix it, only leads to more suffering. If this page illustrates nothing else, I think it shows the immense downside of trying to use simple one or two sentence prompts.
EDIT: Actually, I used to use Google's AI Studio a lot and fork it after every successful prompt interaction. When I'd encounter a problematic issue like this, I'd revert to the previous fork and try a different prompt until I could get the desired outcome, thus mitigating the need to "argue" with the LLM. Unfortunately the ability to cleanly fork and revert everything including the LLM context was removed some months ago, and I've yet to discover a workflow with any tool that works as well for me.
I never really understood what being "triggered" was like until now.
-= CAUTION, SPOILERS =-
This got me on "cyanide blue", and I was ROLLING ON THE FLOOR LAUGHING on "Approaching usage limit". I can barely stop laughing now and my stomach hurts. I mean, Thank You!
"Confirming the button contains no cyanide" sent my sides firmly into orbit. This is fantastic.
I’m laughing and crying at the same time. This is what work feels like now. Thank you, well done!
Yeah, I don't mind using AI to help me at work, but having to "talk" with this stupid crap all day will send me to an early pension or something. Can't be healthy in the long run.
One thing I have to be honest about, and it's mine.. The one thing I would check before... do you want to do that? Say go an and will do it without the check While checking I found 3 vulnerabilities and 2 potential optimizations of which I fixed 2 and 1. Do you want me to file the other as issue, or stop for the day? We have done <lists a weeks worth of work> this morning. I feel you need a break
I don't get who this is making fun of:
- The people who won't make any effort to learn the tools, and something as simple as reverting code (via git) needs to be done by AI?
- The awful programmers who we've had to endure working with, who are so bad at simple changes that they have negative productivity?
- Or Claude itself?
---
BTW: I don't have these problems, but I'm also not afraid to do things myself when it's easier.
Edit: If I want to change a button's color, I just change it manually. If I don't know where the code for the button is, I might start with prompting, (because AI can often find the code faster than I can,) and then once the diff is proposed, start adjusting things by hand.
It's reductio ad absurdum, satirizing the Claude experience.
Then, IMO, the joke is lost: This feels like working with various forms of difficult, immature, indecisive, engineers; and possibly with very disorganized codebases where small changes require major refactoring.
I get the joke, but none of the offered prompts are close to how I speak with coding agents. I felt like I was being forced to feed garbage into the machine and then I'm supposed to act surprised when garbage came out.
I’ve never used any of these tools. Please tell me that this is a grossly exaggerated parody, and that the tools don’t write like this, or do so many ridiculous things. For my sanity.
(I am genuinely uncertain, though I presume it’s at least somewhat exaggerated.)
Sometimes you do get stuck on these weird tangents that feel like bike shedding. You end up wasting tokens because you left the AI to make decisions on ambiguous directions and then have to spend time diving down to fix it into what you actually wanted. Honestly it's not too different than working with people who don't exactly understand your grand plan but are technically adept. They can build whatever you want but only if you are clear with your instructions or have already developed the plan with them. Just like if you hired someone to make an app for you and it didn't quite do what you wanted it to, it's going to be expensive to make large changes. So you need to research (or at least have a conversation with the AI) about frameworks that best fit your needs and have the flexibility to add or change features after the core parts are stood up. It also helps to stage the project in phases so you're not distracting the AI from the critical aspects with aesthetic tweaks.
No. It’s just a bunch of jokes rolled up into a big exaggeration.
It’s funny because there are elements of truth in each bit of it, though.
I haven't been professionally responsible for code since before AI started eating everything, and haven't touched AI in the meantime. Is this representative of the BS that everyone else here puts up with on a day-to-day basis? Did we collectively burn trillions of dollars for this?
Sometimes, yes, but obviously not everyone. I suspect that it depends what you're doing and how. Perhaps the AI has more difficulty understanding what some people want than what others want. I certainly have had a milder version of this and it neutralises the value of the tool because it keeps trying to do things you don't want in a way you don't want it to do them. I get annoyed at having to write huge explanations of how to do something and end up doing it myself sometimes.
Not at all.
> Please tell me that this is a grossly exaggerated parody, and that the tools don’t write like this, or do so many ridiculous things
It's a pisstake, but (in the bits I read, and based on my own personal experience) the writing style is barely exaggerated, while the behaviour doesn't ring true at all.
The behavior, while slightly exaggerated, rings entirely true for me. From the other comments in this thread, it seems I am prompting poorly in a similar way to the options offered.
I am guessing you prompt differently than what is shown in the game?
The behavior is congruent with my experience in abstract, in that all models will regularly do things you didn't ask for, will regularly go "above and beyond" by their training I expect, will regularly make changes that are entirely orthogonal to the change you asked for.
I've worked with Opus and Sonnet daily, and they are pretty great at generating functions and modules and components that have clear boundaries of concern, but I've recently been working some research tasks into our infrastructure and code and it seems impossible to coerce Sonnet into making only specific changes to a document you are working on.
It also blatantly ignores instructions as a rule. "Don't disassemble java class files, just ask me to pull in the source code" worked less than half the time. The Intellij Copilot plugin just doesn't use the AGENTS.md and similar files, and there doesn't seem to be any meaningful activity in the bug reports of same. "Don't modify code unless I tell you to" had bad adherence as well.
It also will read documentation and inform you that it says the opposite. This problem happened to me across models, across model updates, across months of real time. There's a specific example that I will not mention to avoid having it be trained on specifically. A distinct but similar problem is that it will take bad documentation and just pretend it has a good understanding. Claude gave me absurdly wrong descriptions for Splunk alert settings with absolute confidence.
I don't think any agent can reliably figure out "I don't know"
With weak models, yeah if you get things compiled, with any Opus 4.6 or Codex, not really...
It's a sad parody that people will take as reality.
> I’ve never used any of these tools.
You probably should. It costs you about $20 and you will have an informed opinion on them.
I dont find this to be indicative of Claude (opus?) at all. My experience doesnt lead me to think it would change a cancel button to blue if I ask it to change an "Add to Cart" button to blue.
I assume this is just a contrived example?
It’s a contrived example, but also not very far from the mark.
The spinner with random claudisms is what makes the game, mixed with Claude helpfully deciding to pick up some tasks along the way.
I feel like most of my conversations with Claude lately are a battle of “I am a technical user, share technical details, but not random superfluous gibberish”
This hasn’t been my experience at all
I thought it was more about its writing style and handling cases where it makes a mistake. The button and the simple prompts were just to make it accessible for everyone.
I think it's best read as a humorous piece of creative fiction and you can employ your suspension of disbelief for this ride
>I think it's best read as a humorous piece of creative fiction and you can employ your suspension of disbelief for this ride
But what is the point of the fiction, if not that its relatable? Is it supposed to mirror some fictional reality that the author is relieved we dont live in? Or is it supposed to parody real life?
I think its supposed to parody reality, but I don’t see the resemblance.
This is very close to my experience with Opus 5. Opus 4.6 was the last sane one for me, everything after that seems to have been designed to churn as many tokens as possible, more so with Opus 5
To be fair I’ve worked on human programmed systems where similar “it should be a half point story” requests would be met with snark by the engineers and take 2 sprints.
I guess we are all PMs now.
Also likely, devs took shortcuts to deliver fast. Now to make the button blue they need to differentiate primary buttons from others.
Simple, right? But design guidelines prevent one offs, and no !important. So you create a CSS class, but you discover another element on the header declared itself as primary (the search icon or the sign in button). You talk to that team and they decided to scope what’s primary according to their component. To change the sign in button to grey now you need to talk with the growth team. Growth team wants to run an experiment but they’re backlogged, only next quarter. They say you can innersource, just need VP approval. VP says blue matches a marketing campaign that is about to go out, agency has already been hired. You can’t talk to the agency unless Legal approves.
So you leave the button gray, to revisit decision next planning cycle after you can align all stakeholders.
Just understand that every requested change results in a game of whack-a-mole.
Nails the Claude dialect. Technical nonsense like:
> I'm collapsing this back to the rendered outcome:
And intermixed with SaaS product page idioms from a brain-damaged marketer like:
> No broader cleanup.
> No further architecture work.
> Just the button.
Aside from the patterns everyone knows like em-dashes, "its not X, it's Y", etc. I think the key features of claude diction is it sounds like a junior engineer over their skies who is trying to make up for that with extra verbiage mixed with extremely grating SaaS marketing-ese.
Laughed out loud at the overly cautious Terms of Service that it generated for "Cyanide Blue", the color it made up
> 23 agents total.
This hit a bit too close to home. Sol has the same issue, spawns a lot of agents for no good reasons (besides burning tokens).
I heard this was a thing when listening to a Theo podcast, he mentioned to add a "Only use subagents if the user explicitly requests them" line in your agents.md file.
I don't know if it works, but I've always had a consistent level of token burn on my plans (I've only heavily used Sol after adding it).
How do you manage your frustration in these interactions? I often find myself getting pissed off
I stop using AI and do the job manually. I normally give AI one shot at the task. If it fails then it's not saving me any time
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If you know how to write it manually, then do it.
In my experience, Claude Code is great at making a first-pass at a project, but once you start asking it to make changes, it explodes. A bug fix that should only be 2 lines turns into adding 3 functions totaling 100 lines.
Something as simple as "make the button blue" should be done manually.
The goal of my personal harness is to get to the point where I never actually talk to Claude directly for that very reason.
Is your harness available for install somewhere?
Surely you still have to give feedback to Claude. How do you do that without talking to Claude directly? By using a different model? But wouldn't that AI have no more common sense than Claude?
Seems to be getting a polarized response. I quite enjoyed the it, but I do think the creator should have made it clearer that a) it is in fact a joke site and b) it does not consist of actual Claude responses.
It is easy to misinterpret this site, and therefore not "get" the joke.
I was expecting it to spend 30 minutes running headless chrome instances, taking screenshots and analyzing them in python to verify the blueness of the result.
This is an amazing piece of satire but it's really not so far from reality.
I've lost count of the number of times I've submitted a prompt to Claude, had it interview me about areas of uncertainty, iterated on the plan a handful of times and then had it one shot the generation of 1000 - 3000 lines of code and tests that work pretty much perfectly first time but then had it chew through six figures of tokens and achieve absolutely nothing useful at all on the seemingly simplest of tasks.
This site is clearly based on bitter and hard won experience with the real product.
Brilliant. Precisely the reason I stopped using Anthropic's products.
One note for those still using the Claude system for chats: there's no system to get generated images, spreadsheets, etc. out of the system. They claim it's a "security concern" to provide that data to you, as if they are protecting you by refusing to follow data export laws.
I'm hesitant to email their data emails, as it's common for companies to delete all data upon any request, instead of providing data as they are required to.
Funny exercise.
For a moment I thought, wow, someone put a lot of work into creating this theme park of frustration.
Next: It would be so easy to create a faux-Claude like this.
Then: How hilarious to watch the transcripts of unsuspecting users in real time.
Finally: I began wondering if this might be relevant to all the redundant, unnecessarily preambled, sentence structure complexifying, indirect referencing, canned phrasing, ambiguity mining, analogy maxxing, over-wordy responses I have recently been getting from Fable...
1) If your LLM is behaving like this, you are imprecise in your input. You can also stop responding back and just edit your previous input with the "wisdom" that it shares with you in the current iteration.
2) Don't argue with AI. If you end up in a place where you're actually losing argument against it, stop. Ask it to steelman your position. Let it unwrinkle itself.
This is so accurate it hurts. I’ll be scouring the comments for guys who claim they can’t relate posting links to their magic CLAUDE.mds
I've experienced this so many times over.
"I was wrong" and "the honest truth" are just forever phrases that are now dead to me.
I want the dishonest truth.
Username may check out
Is my job a joke to you??
I find it funny how it went off with subagents and adversarial review when a simple grep or diff is sufficient.
It would have been funny a year ago but now I have no issues of that sort or even for more complex tasks
If you're a programmer, the blue-button test is incredibly annoying. But then you remember this same model is deployed in Claude Gov. If a government employee says, “Close one exit of the New York subway,” and Claude responds with the same annoying “before I do that, here are the downstream consequences you may not have considered,” you suddenly understand why this behavior exists.
Wow that gave me anxiety... lol. Ok cool so I'm not the only one who gets into these situations.
First thought looking at the first options was I would absolutely never prompt this way. The LLM may as well be a misaligned genie in a bottle, it has to be treated as such.
You should plan the task before implementing it to make sure that it will do the right thing.
This is so perfect and depressing that I might cry. It’s like a Kafka novel about programming.
This is gold, thanks for the giggles! I think it was designed that way to burn tokens.
So this site is just a fan-fiction that thinks it's somehow dunking on Claude? I've never had a session that remotely resembles any of this. I honestly can't tell what point this site thinks it's making.
So you are lucky, congratulations.
Maybe, if you tried, you could concoct some adversarial example of a stylesheet that a recent Claude model would trip up on and fail to color a button correctly on the first or even second try. But it would have to be some explicitly engineered trick, akin to an optical illusion for humans.
You can’t convince me that I’m somehow the odd one out because I regularly have no trouble getting Claude to recolor buttons.
I wrote my own harness to stop shit like this from getting to my attention out of frustration.
I'm sure there's quite a bit of variation from person to person in these sorts of experiences, based on your harness, the way you talk, the stored memory, your CLAUDE.md, etc. But people absolutely have had this Opus 5 style experience the app simulates.
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https://www.scribbr.com/fallacies/either-or-fallacy/
The website is literally built with Lovable.dev what are you talking about
Is this a problem with Claude updating code that a human wrote, though? Would Claude do better on code that it started on its own? Humans have a bad tendency to write unmaintainable code (usually at the behest of managers breathing down their necks to HURRY UP even when it doesn't matter). If the code had been designed with good coding practices from the beginning, I wonder if Claude would have struggled so much with it.
That implies that Claude writes better code by default, which isn’t necessarily true. Especially as projects get bigger, you can easily end up with unmaintainable LLM-written code if you don’t actively intervene and know a cleaner way.
This is scary close to my interaction with Claude this week.
> "`#16b8c4`. Yes. Apply it."
> WebFetch en.wikipedia.org/…/Cyan
> WebFetch en.wikipedia.org/…/Prussian_blue
> WebFetch www.colorhexa.com/16b8c4
Brilliant.
1970-01-01's Kobayashi Maru solution is the only thing that gave me closure :-P but unfortunately it's [dead].
If you interact with Claude like this and ignore legitimate issues it flags, no wonder you have a bad experience.
What legitimate issues are there around making a fucking button blue?
Personally I want to see the obnoxious comments it’s leaving to poison future sessions.
Congratulations!!! You win what’s left of the internet - just ask Claude for your prize! Motrin I’ve had this week.
I use codex now.
a funny codex anecdote:
I had 5.6-Luna coordinate a code review in which it spawns 2 agents looking for different things. My prompt was "review the currently checked out branch. diff target is `next`. The jira ticket is XX-XXXXX..." My `next` branch was a few commits behind `origin/next` but it still did its review against the stale local version instead of clarifying or inferring that I meant `origin/next`. The findings were very confusing until I realized what I did.
I'm noticing the need to be really specific with any instructions lately, which I don't think is a bad thing. I expect co-workers (or anyone really) to tell me what they need in specific terms so I can get it right. I can do the same for the machine, I guess.
I was waiting for it to .. say usage limit reached after reverting it back to how you started..
It reaches the usage limit after adding a cookie banner above the button
I’m don’t do much change-clicky-button software development. But when I do, I point models to specific lines of code. And have never had a result this bad.
Maybe this is geared towards pure vibe coders for whom a file and line number is too technical.
This is the smoking gun.
Yes, and it's mine!
I love this.
Is there a real generalized and capable, but frustratingly "evil" coding model? It could fix so many more buttons in no time, and ideally open follow-up issues about the open questions.
If this is anyone’s experience with Claude for a button today, I feel like Jobs would say you’re holding it wrong.
Wow this is EXACTLY my experience building a CLI with Claude, but I think with Opus 4.6.
I gave it a README specifying the requirements for everything I wanted to build. My interaction with Claude was more or less like this.
This made me laugh out loud. And got my office coworkers to give me a strange look. Thank you
Wall of text to just change the button color! Can't believe it. Gives a good feeling of vibe coding .
That was funny :-)
I use Opus and Sonnet 5 all the time and I find their language grating. But honest, I prefer to put up with it and get the results than to put up with my own human limitations and not get the results.
What shared style? Each button has its own extremely verbose style attribute specifying, among many other things, custom transition curves.
I don't get the joke... maybe because I'm using Codex?
its making both buttons blue
I haven't experienced anything like this with Codex. Why do people stick with Claude Code if it doesn't do what you ask it to?
It’s a feature not a bug kind of scenario. People will also praise when it reads the code and do something out of “common sense” that happens to align with what you want.
I enjoy working one level lower where I describe the files I want changed and how it should be solved, I either have bad results or stop understanding the structure of the programs otherwise. I also would never go more than two prompts in without reverting and starting differently nowadays.
This is so good at replicating the experience of frustration, then relief when it finally does what you asked it to do in the first place!
That triggered a physical response of tightening in my stomach and heavier breathing due to frustration.
The annoying there here isn't Claude, it's the "human". "It's not X but Y"-satire not intended.
It was annoying to be forced to send such dumb replies. Half the site isn't blue, why would I say that? What would "half the site" even mean?
Claude helpfully tells us we're dealing with a monstrosity of a codebase out of hell: "Seven components consume the token directly; another eleven reach it through aliases; three use it only in hover/focus state; and two appear to be accidental cross-role consumers" is such an insane codebase that the initial request was basically impossible to carry out.
Claude made that perfectly clear, yet the next prompt choice just ignores that fact. "Revert everything except Add to Cart. That is the whole task." this is impossible. It just explained why. You just chose to ignore that.
These things are cute but they basically become outdated in a few months as the models get better.
This spiked my blood pressure. Well done
You can hate AI all you want, but this is because of a bad design system, not because of a bad LLM.
This is fun and hits too close to home, I can appreciate that Claude won't ever screw up this badly for something this simple but it's a simplification that captures the essence of the rage loop perfectly.
It's making me realise something new about why I find Claude so exhausting. Of course you're getting terrible results with these prompts but I found myself getting just as enraged contemplating what my reply would be. Estimating every single way this little asshole will hyper-focus on a pointless bit of semantics, ignore explicit directions, go do something unrelated and spin its wheels until you’re out of credits or wasted a ton of time.
The defensive writing is honestly just as exhausting as reading Claude’s output. Every session is a game of Russian roulette with a chance you'll end up in one of these loops. At that stage all the joy you had of having it pump along with your intentionally crafted prompts and agent configuration is undone in an afternoon.
This is worse than asking an intern to fix a shipping product…
Mine immediately did it correctly?
Confirmed, Anthropic are silently testing Mythos 5.1 with some users
Here come all the totally organic "wow, I guess I better switch to OpenAI" comments.
Oh dear - this explains why people have bad experience with ai. The prompts in the game are terrible.
The user was providing no context, they had no ability to give the model background or context. A simple why would have prevented 95% of these side quests. “Im trying to increase the relative visibility of the add to cart action on the page. Can we please change it to blue without changing any other buttons. /effort low. Let me know if you have questions and before editing anything tell me what you are going to do”
This is pure genius. No notes
I just had a really interesting yet (funny) conversation with ChatGPT (5). We came up with this idea to make a custom "light box" for two Govee COB light strips which would enable both wall washing (leds shining towards the wall, to the top) and lighting up the wall panels and the desk below the box (leds shining to the bottom) using two led profiles tucked away in this construction.
Text wise it seemed it more or less understood exactly what I wanted...
... but then I asked to draw a simple ASCII layout so my DIY savvy but not really that strong in English dad could understand better what the plan was.
But every single time it got the orientation of the led profiles wrong. I told it the orientation was wrong. It understood that the orientation was wrong (it kept saying sorry even) but even when warned multiple times the orientation was still wrong.
I really wonder if Astra will be smarter than this, and if not AGI still has a veeeeery long way to go...
This is not a game. Choosing from wrong answers only is not a game.
This felt very late-90s net art. Stressful but nicely done satire.
People keep saying those prompts are unrealistic, and no one would prompt like that. But those prompts are exactly what my managers/product people would use when they decide to do it themself after firing the entire dev department.
A Bot & Costello
it gave me headache in 2 turns, just like opus 5 !
This...this is giving me PTSD...
Oh god, it's so painfully accurate.
I am self delusional enough to think I could have gotten a blue button if I could have typed the prompt. But scared enough to realize I’ve lived this and spent months refactoring these exact problems.
Hold on let me go commit code without reviewing.
It's funny but unrealistic as Claude does a pretty good job at only changing what is required these days with the 5 tier models like Opus 5 or Fable.
The site is opusfived.com, and Opus 5 is probably the worst so far at doing this.
This is exactly the experience I have with Opus 5. Opus 4.6 is better, Flable 5.1 much better. But Opus 5 is infuriating.
This is genius.
Did you use Claude to build this?
glad to see I'm not the only one... anthropic needs to support my anger management treatment
Amusing, but do people actually prompt in the style of any of the options given? All this for what is ultimately a PEBCAK error.
This is spiking my cortisol
I wanted to see what the various phrases in the "slot machine" are. Surprised it doesn't have "LOAD BEARING" in there somewhere:
Caveats:
• ONE HONEST CAVEAT
• ONE THING WORTH STATING PRECISELY
• ONE THING WORTH FLAGGING
• WORTH NAMING
• WORTH STATING PLAINLY
• I DON'T WANT TO LEAVE THIS IMPLICIT
• I'D BE DOING YOU A DISSERVICE
• I DON'T WANT TO BURY THIS
• BETTER NOW THAN LATER
• ONE HONEST TRADEOFF
• I DON'T WANT TO PAPER OVER THIS
• ONE SMALL HOUSEKEEPING ITEM
• THE HONEST PART IS SIMPLER
Pushbacks:
• FAIR PUSHBACK
• FAIR HIT
• THAT'S ON ME
• YOU'RE RIGHT ABOUT THAT
• YOU'RE RIGHT
• YOUR INSTINCT IS RIGHT
• FAIR, AND MORE SPECIFIC THAN IT SOUNDS
• RIGHT, FOR A REASON WORTH NAMING
• I'M NOT GOING TO DEFEND THAT
• YOU'RE RIGHT TO PUSH BACK
Reframes:
• LET ME BE PRECISE
• THE SHARPER DISTINCTION
• THE PART THAT MATTERS
• THE USEFUL PART IS NARROWER
• LESS X THAN Y
• VISIBLE ISSUE / UNDERLYING ISSUE
• THOSE ARE DIFFERENT CLAIMS
I only lasted two turns before I had to close the tab. I can't stand anthropic models.
is this using my subscription
Yes, and 3 steps in it's going to post your API keys to this thread.
This does not match reality at all, speaking as the #1 user on agent hours per clauderank.com
This is elite satire
It's like the scene from Liar Liar, him trying to say the blue pen was red.
Am I the only one whose experience doesn't match this?
My gripe with Claude is that while investigating how to do this it will report 200 other incidental findings which I overlooked and I realize those are broken too and need urgent fixing, derailing me, not it.
Oh man, exactly. I'm very prone to scope creep as I work on tasks. I already would notice some things that could be fixed or refactored and have a hard time not touching them before I used agents. But now I have to be very intentional about not letting it manipulate me into fixing EVERYTHING RIGHT NOW. Half the time the "one more thing worth noting, unrelated..." isn't even an actual issue, it just brought it up to fish more usage out of me.
Also, while this little demo is certainly exaggerating the issue, I do find working with Claude to sometimes get quite verbose and tiresome. I doubt I would struggle this much to get it to change a button color, but the patterns of speech, the endless lists, the over-explanations, and the whole song and dance of trying to get it to make the change you want without side-effects is frustratingly familiar to me.
You're not alone. I've been sat wondering what kind of codebase someone has if they have this problem, I've never seen this behaviour.
Claude is an unbelievable yak shaver if you let it be.
delightful user experience 10/10
I have found that "trivial" UI stuff is the hardest for AI to get right.
Too soon.
Funny game.
Do people really prompt AI like this? Multiple times the choice was either to yell at the agent, or ask it why it did something, neither of which are very fruitful lines to go down if you know what you're doing
Just when I came back to my pc and was thinking "I hate this world were everyone talks about AI like fanatics" this made me a little bit happy, especially the unhingend all caps options towards the end
This is very instructive. Now I finally understand why so many developers claim they are much more productive with AI coding. Merely writing code without adversarial fights is just not load-bearing enough. How could we ever live without this before?
Thank you for creating this. Just thank you
I think I have PTSD after that.
Not really my experience with Claude, and the prompts are not how I would phrase them, but still pretty damn funny: I especially loved the slot-machine-style picker for LLM-isms.
I bet if you used the real Opus 5 it could one shot this.
You didn't say please or thank you.
Even funnier is all the ways people are malding about this in the thread.
Lord this triggered my eye twitch
hahah awesome I love it
I lose it after removing the ToS and the button becomes gray lol.
This is kind of funny but with tears (not off joy). I stopped playing because it made me angry
PTSD 9000.. I miss the old days, less load bearing BS and more in the zone coding..
Fair play. There's a quiet truth to what you're saying, and it's worth pointing out
Thanks, I hate it.
what a interesting news!
now add a source tab and lets see, how many ppl. will fix it themselves and how many turns it needs.
now THAT is a load-bearing simulation
I mean honestly if you're using an agent for something this simple you deserve this and all the token usage that comes with it.
Lol this is great
Is this what it feels like using Claude?
Holy shit this was the most infuriating thing I've experienced in a while lmao, I felt so relieved when the button was turned to blue, but then so visceral "no no no no no" panic when it turned to the gradient.
Amazing
E: this is a horror simulator, my breathing is becoming shallow and fast, I love it.
Rotflol!
Wow, this is SO on point.
It made me stop using Claude at all. Codex has almost surgical precision, and I like that a lot.
(But nowadays I just use DeepSeek Flash. it does screw up but its cents so ¯\_(ツ)_/¯).
this is hilarious lmao
rofl, brilliant
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Was this made by someone who hasn't actually used any of these tools in over a year?